检索结果-内蒙古大学图书馆

SSRN 2024年

作者： Lamm, Erik D. Babler, Kristina M. Sharkey, Mark E. Amirali, Ayaaz Beaver, Cynthia Boone, Melinda M. Comerford, Samuel Cooper, Daniel Currall, Benjamin B. Grills, George S. Kobetz, Erin Kumar, Naresh Laine, Jennifer Lamar, Walter E. Lyu, Jiangnan Kennedy, Althea Perritano, Stefan Mason, Christopher E. Reding, Brian D. Roca, Matthew A. Schürer, Stephan C. Shukla, Bhavarth S. Solle, Natasha Schaefer Tallon, John J. Thomas, Collette Tierney, Braden T. Torres, Belkis Venkatpuram, Sreeharsha Vidovic, Dusica Williams, Sion L. Yin, Xue Zarnegarnia, Yalda Solo-Gabriele, Helena M. Department of Chemical Environmental and Materials Engineering University of Miami Coral GablesFL United States Department of Medicine University of Miami Miller School of Medicine MiamiFL United States Sylvester Comprehensive Cancer Center University of Miami Miller School of Medicine MiamiFL United States DataGrade Solutions LLC MiamiFL United States Department of Public Health Sciences University of Miami Miller School of Medicine MiamiFL United States Environmental Health and Safety University of Miami MiamiFL United States Division of Occupational Health Safety & Compliance University of Miami Health System MiamiFL United States Department of Physiology and Biophysics Weill Cornell Medical College New York CityNY United States The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine Weill Cornell Medicine New YorkNY United States The WorldQuant Initiative for Quantitative Prediction Weill Cornell Medicine New YorkNY United States Department of Molecular & Cellular Pharmacology University of Miami Miller School of Medicines MiamiFL United States Institute for Data Science & Computing University of Miami Coral GablesFL United States Facilities and Operations University of Miami Coral GablesFL United States

Measurements of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in wastewater can be used to understand the prevalence of COVID-19 cases within a community. Environmental conditions inclusive of water quality are known to impact wastewater SARS-CoV-2 signals, but they are rarely measured in areas upstream of wastewater treatment plants. The objectives of this study were to report on continuous measurements of environmental parameters (water quality and flow) in the upper reaches of a sewershed and to evaluate whether the inclusion of these environmental parameters improves associations between SARS-CoV-2 RNA levels in wastewater, and COVID-19 prevalence in the sewershed community. Measurements of environmental parameters and SARS-CoV-2 RNA in wastewater spanned different time scales (minutes, hours and weeks) and population scales (building, campus, community). Spearman correlations and stepwise regressions were used to evaluate associations. When comparing SARS-CoV-2 RNA levels directly to environmental parameters from instantaneous measurements or grab samples, results showed inconsistent correlations likely due to short term (minute-scale) variations observed in flow and water quality. For the analysis involving COVID-19 prevalence data which required averaging over weekly time scales, regressions showed that inclusion of environmental parameters, in particular pH, improved correlations between RNA and COVID-19 prevalence. The significance of pH in improving correlations of SARS-CoV-2 with prevalence data was greater for the cluster sewershed scale (populations of a few thousand) than at the community scale (populations of several 100,000). The significance of pH is believed to be related to the properties of the tap water characterized by high pH and low alkalinity, with pH serving as a proxy of fecal waste allowing for an adjustment of the SARS-CoV-2 signal to account for human waste dilution within the sewer system. © 2024, The Authors. All rights

关键词： Coronavirus

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A field guide to cultivating computational biology

arXiv

引用

arXiv 2021年

作者： Carpenter, Anne E. Greene, Casey S. Carninci, Piero Carvalho, Benilton S De Hoon, Michiel Finley, Stacey Lê Cao, Kim-Anh Lee, Jerry S.H. Marchionni, Luigi Sindi, Suzanne S. Theis, Fabian J. Way, Gregory P. Yang, Jean Y.H. Fertig, Elana J. Imaging Platform Broad Institute of Mit and Harvard CambridgeMA United States Center for Health Ai University of Colorado School of Medicine AuroraCO United States Human Technopole Via Belgioioso 171 Milano MI20157 Italy Department of Statistics Institute of MathematicsStatistics and Scientific Computing University of Campinas Campinas Brazil Riken Center for Integrative Medical Sciences Yokohama Kanagawa Japan Department of Biomedical Engineering Quantitative and Computational Biology Chemical Engineering & Materials Science University of Southern California United States Melbourne Integrative Genomics School of Mathematics and Statistics University of Melbourne Australia Departments of Medicine/Oncology Chemical Engineering and Material Sciences University of Southern California CA United States Department of Pathology and Laboratory Medicine Weill-Cornell Medicine New YorkNY United States Department of Applied Mathematics University of CaliforniaMerced MercedCA United States Helmholtz Center Munich and Department of Mathematics Institute of Computational Biology Technical University of Munich Germany Charles Perkins Centre and School of Mathematics and Statistics University of Sydney Australia Departments of Oncology Convergence Institute Biomedical Engineering and Applied Mathematics and Statistics Johns Hopkins University BaltimoreMD United States

Biomedical research centers can empower basic discovery and novel therapeutic strategies by leveraging their large-scale datasets from experiments and patients. This data, together with new technologies to create and analyze it, has ushered in an era of data-driven discovery which requires moving beyond the traditional individual, single-discipline investigator research model. This interdisciplinary niche is where computational biology thrives. It has matured over the past three decades and made major contributions to scientific knowledge and human health, yet researchers in the field often languish in career advancement, publication, and grant review. We propose solutions for individual scientists, institutions, journal publishers, funding agencies, and educators. © 2021, CC BY-SA.

关键词： Large dataset

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Analysis and approximations of dirichlet boundary control of stokes flows in the energy space

arXiv

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arXiv 2020年

作者： Gong, Wei Mateos, Mariano Singler, John R. Zhang, Yangwen State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics National Center for Mathematics and Interdisciplinary Sciences Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Dpto. de Matemáticas Universidad de Oviedo Campus de Gijón Spain Department of Mathematics and Statistics Missouri University of Science and Technology RollaMO United States Department of Mathematical Science University of Delaware NewarkDE United States

We study Dirichlet boundary control of Stokes flows in 2D polygonal domains. We consider cost functionals with two different boundary control regularization terms: the L2 norm and an energy space seminorm. We prove well-posedness and regularity results for both problems, develop finite element discretizations for both problems, and prove finite element error estimates for the latter problem. The motivation to study the energy space problem follows from our analysis: we prove that the choice of the control space L2(Γ) can lead to an optimal control with discontinuities at the corners, even when the domain is convex. We observe this phenomenon in numerical experiments. This behavior does not occur in Dirichlet boundary control problems for the Poisson equation on convex polygonal domains, and may not be desirable in real applications. For the energy space problem, we derive the first order optimality conditions, and show that the solution of the control problem is more regular than the solution of the problem with the L2(Γ) regularization. We also prove a priori error estimates for the control in the energy norm, and present several numerical experiments for both control problems on convex and nonconvex domains. © 2020, CC0.

关键词： Poisson equation

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Anticipative tracking with the short-Term synaptic plasticity of spintronic devices

arXiv

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arXiv 2020年

作者： Zheng, Qi Mi, Yuanyuan Zhu, Xiaorui Yuan, Zhe Xia, Ke Center for Advanced Quantum Studies and Department of Physics Beijing Normal University Beijing100875 China Center for Quantum Computing Peng Cheng Laboratory Shenzhen518005 China Center for Neurointelligence Chongqing University Chongqing400044 China Center for Artificial Intelligence Peng Cheng Laboratory Shenzhen518005 China Beijing Computational Science Research Center Beijing100193 China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and Technology Shenzhen518055 China

Real-Time tracking of high-speed objects in cognitive tasks is challenging in the present artificial intelligence techniques because the data processing and computation are time-consuming resulting in impeditive time delays. A brain-inspired continuous attractor neural network (CANN) can be used to track quickly moving targets, where the time delays are intrinsically compensated if the dynamical synapses in the network have the short-Term plasticity. Here, we show that synapses with short-Term depression can be realized by a magnetic tunnel junction, which perfectly reproduces the dynamics of the synaptic weight in a widely applied mathematical model. Then, these dynamical synapses are incorporated into one-dimensional and two-dimensional CANNs, which are demonstrated to have the ability to predict a moving object via micromagnetic simulations. This portable spintronicsbased hardware for neuromorphic computing needs no training and is therefore very promising for the tracking technology for moving targets. Copyright © 2020, The Authors. All rights reserved.

关键词： Data handling

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Sensor selection for hyper-parameterized linear Bayesian inverse problems

引用

PAMM 2021年第S1期20卷

作者： Nicole Aretz Peng Chen Karen Veroy Aachen Institute for Advanced Study in Computational Engineering Science (AICES) RWTH Aachen University Schinkelstr. 2 52062 Aachen Germany Oden Institute for Computational Engineering and Sciences University of Texas at Austin 201 E 24th St Austin TX 78712 USA Centre for Analysis Scientific Computing and Applications Eindhoven University of Technology Groene Loper 5 5612 AZ Eindhoven The Netherlands

Models of physical processes often depend on parameters, such as material properties or source terms, that are only known with some uncertainty. Measurement data can be used to estimate these parameters and thereby improve the model's credibility. When measurements become expensive, it is important to choose the most informative data. This task becomes even more challenging when the model configurations vary and the data noise is correlated. In this poster we summarize our results in [1] and present an observability coefficient that describes the influence of the sensors on the inverse solution. It can guide optimal sensor selection towards a uniformly good parameter estimate over all admissible model configurations. We propose a sensor selection algorithm that iteratively improves the observability coefficient, and present numerical results for a steady-state heat conduction problem with correlated noise.

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Analysis of the second order bdf scheme with variable steps for the molecular beam epitaxial model without slope selection

arXiv

引用

arXiv 2020年

作者： Liao, Hong-Lin Song, Xuehua Tang, Tao Zhou, Tao Department of Mathematics Nanjing University of Aeronautics and Astronautics Nanjing211106 China Department of Mathematics Nanjing University of Aeronautics and Astronautics 211101 China Department of Mathematics and International Center for Mathematics Southern University of Science and Technology ShenzhenGuangdong China Division of Science and Technology BNU-HKBU United International College ZhuhaiGuangdong China NCMIS & LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

In this work, we are concerned with the stability and convergence analysis of the second order BDF (BDF2) scheme with variable steps for the molecular beam epitaxial model without slope selection. We first show that the variable-step BDF2 scheme is convex and uniquely solvable under a weak time-step constraint. Then we show that it preserves an energy dissipation law if the adjacent time-step ratios rk := τk/τk−1 2 norm stability and rigorous error estimates are established, under the same step-ratios constraint that ensuring the energy stability., i.e., 0 k MSC Codes 65M06, 65M12 Copyright © 2020, The Authors. All rights reserved.

关键词： Number theory

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Framing image registration as a landmark detection problem for label-noise-aware task representation (HitR)

arXiv

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arXiv 2023年

作者： Waldmannstetter, Diana Ezhov, Ivan Wiestler, Benedikt Campi, Francesco Kukuljan, Ivan Ehrlich, Stefan Vinayahalingam, Shankeeth Baheti, Bhakti Chakrabarty, Satrajit Baid, Ujjwal Bakas, Spyridon Schwarting, Julian Metz, Marie Kirschke, Jan S. Rueckert, Daniel Heckemann, Rolf A. Piraud, Marie Menze, Bjoern H. Kofler, Florian Department of Computer Science TUM School of Computation Information and Technology Technical University of Munich Munich Germany Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Department of Diagnostic and Interventional Neuroradiology School of Medicine Klinikum rechts der Isar Technical University of Munich Germany Helmholtz AI Helmholtz Munich Neuherberg Germany TranslaTUM - Central Institute for Translational Cancer Research Technical University of Munich Germany Healthcare Technologies SETLabs Research Munich Germany Department of Oral and Maxillofacial Surgery Radboud University Nijmegen Medical Centre Nijmegen Netherlands Division of Computational Pathology Department of Pathology and Laboratory Medicine School of Medicine Indiana University IndianapolisIN United States Department of Electrical and Systems Engineering Washington University in St.Louis St. LouisMO United States Artificial Intelligence in Healthcare and Medicine Technical University of Munich Munich Germany Department of Computing Imperial College London London United Kingdom Department of Medical Radiation Sciences University of Gothenburg Gothenburg Sweden

Accurate image registration is pivotal in bio-medical image analysis, where selecting suitable registration algorithms demands careful consideration. While numerous algorithms are available, the evaluation metrics to assess their performance have remained relatively static. This study addresses this challenge by introducing a novel evaluation metric termed Landmark Hit Rate (HitR), which focuses on the clinical relevance of image registration accuracy. Unlike traditional metrics such as Target Registration Error, which emphasize sub-resolution differences, HitR considers whether registration algorithms successfully position landmarks within defined confidence zones. This paradigm shift acknowledges the inherent annotation noise in medical images, allowing for more meaningful assessments. To equip HitR with label-noise-awareness, we propose defining these confidence zones based on an Inter-rater Variance analysis. Consequently, hit rate curves are computed for varying landmark zone sizes, enabling performance measurement for a task-specific level of accuracy. Our approach offers a more realistic and meaningful assessment of image registration algorithms, reflecting their suitability for clinical and biomedical applications. Copyright © 2023, The Authors. All rights reserved.

关键词： Medical imaging

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Doped NiO: The Mottness of a charge transfer insulator

arXiv

引用

arXiv 2020年

作者： Wrobel, Friederike Park, Hyowon Sohn, Changhee Hsiao, Haw-Wen Zuo, Jian-Min Shin, Hyeondeok Lee, Ho Nyung Ganesh, P. Benali, Anouar Kent, Paul R.C. Heinonen, Olle Bhattacharya, Anand Materials Science Division Argonne National Laboratory LemontIL60439 United States Department of Physics University of Illinois at Chicago ChicagoIL60607 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Physics Ulsan National Institute of Science and Technology Ulsan Korea Republic of Department of Materials Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Computational Science Division Argonne National Laboratory ArgonneIL60439 United States Leadership Computing Facility Argonne National Laboratory ArgonneIL60439 United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Center for Hierarchical Material Design Northwestern-Argonne Institute for Science and Engineering Northwestern University EvanstonIL60208 United States

The evolution of the electronic structures of strongly correlated insulators with doping has long been a central fundamental question in condensed matter physics;it is also of great practical relevance for applications. We have studied the evolution of NiO under hole and electron doping using high-quality thin film and a wide range of experimental and theoretical methods. The evolution is in both cases very smooth with dopant concentration. The band gap is asymmetric under electron and hole doping, consistent with a charge-transfer insulator picture, and is reduced faster under hole than electron doping. For both electron and hole doping, occupied states are introduced at the top of the valence band. The formation of deep donor levels under electron doping and the inability to pin otherwise empty states near the conduction band edge is indicative that local electron addition and removal energies are dominated by a Mott-like Hubbard U-interaction even though the global bandgap is predominantly a charge-transfer type gap. Copyright © 2020, The Authors. All rights reserved.

关键词： Nickel oxide

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Color dependence of the topological susceptibility in Yang-Mills theories

arXiv

引用

arXiv 2022年

作者： Bennett, Ed Hong, Deog Ki Lee, Jong-Wan David Lin, C.-J. Lucini, Biagio Piai, Maurizio Vadacchino, Davide Swansea Academy of Advanced Computing Swansea University Fabian Way Wales SwanseaSA1 8EN United Kingdom Department of Physics Pusan National University Busan46241 Korea Republic of Institute for Extreme Physics Pusan National University Busan46241 Korea Republic of Institute of Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Center for High Energy Physics Chung-Yuan Christian University Chung-Li32023 Taiwan Centre for Theoretical and Computational Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Physics Division National Centre for Theoretical Sciences Taipei10617 Taiwan Department of Mathematics Faculty of Science and Engineering Swansea University Fabian Way Wales SwanseaSA1 8EN United Kingdom Department of Physics Faculty of Science and Engineering Swansea University Singleton Park Wales SwanseaSA2 8PP United Kingdom School of Mathematics Hamilton Mathematics Institute Trinity College Dublin 2 Ireland Centre for Mathematical Sciences University of Plymouth PlymouthPL4 8AA United Kingdom

For Yang-Mills theories in four dimensions, we propose to rescale the ratio between topological susceptibility and string tension squared in a universal way, dependent only on group factors. We apply this suggestion to SU(Nc) and Sp(Nc) groups, and compare lattice measurements performed by several independent collaborations. We show that the two sequences of (rescaled) numerical results in these two families of groups are compatible with each other. We hence perform a combined fit, and extrapolate to the common large-Nc limit. © 2022, CC BY.

关键词： Topology

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Sp(2N) Yang-Mills theories on the lattice: scale setting and topology

arXiv

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arXiv 2022年

作者： Bennett, Ed Hong, Deog Ki Lee, Jong-Wan Lin, C.-J. David Lucini, Biagio Piai, Maurizio Vadacchino, Davide Swansea Academy of Advanced Computing Swansea University Fabian Way Swansea WalesSA1 8EN United Kingdom Department of Physics Pusan National University Busan46241 Korea Republic of Institute for Extreme Physics Pusan National University Busan46241 Korea Republic of Institute of Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Center for High Energy Physics Chung-Yuan Christian University Chung-Li32023 Taiwan Centre for Theoretical and Computational Physics National Yang Ming Chiao Tung University 1001 Ta-Hsueh Road Hsinchu30010 Taiwan Physics Division National Centre for Theoretical Sciences Taipei10617 Taiwan Department of Mathematics Faculty of Science and Engineering Swansea University Fabian Way Swansea WalesSA1 8EN United Kingdom Department of Physics Faculty of Science and Engineering Swansea University Singleton Park Swansea WalesSA2 8PP United Kingdom School of Mathematics Hamilton Mathematics Institute Trinity College Dublin 2 Ireland Centre for Mathematical Sciences University of Plymouth PlymouthPL4 8AA United Kingdom

We study Yang-Mills lattice theories with Sp(Nc) gauge group, with Nc = 2N, for N = 1, ···, 4. We show that if we divide the renormalised couplings appearing in the Wilson flow by the quadratic Casimir C2(F) of the Sp(Nc) group, then the resulting quantities display a good agreement among all values of Nc considered, over a finite interval in flow time. We use this scaled version of the Wilson flow as a scale-setting procedure, compute the topological susceptibility of the Sp(Nc) theories, and extrapolate the results to the continuum limit for each Nc. © 2022, CC BY.

关键词： Lattice theory

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